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Record W1999417024 · doi:10.5539/jmr.v2n1p52

Application of Meshless Natural Neighbour Petrov-Galerkin Method in Temperature Field

2010· article· en· W1999417024 on OpenAlexvenueno aff
Dongmei Li, Maohui Xia, Yu Chen, Zitao Xu

Bibliographic record

VenueJournal of Mathematics Research · 2010
Typearticle
Languageen
FieldEngineering
TopicNumerical methods in engineering
Canadian institutionsnot available
Fundersnot available
KeywordsPetrov–Galerkin methodMathematicsRegularized meshless methodGalerkin methodInterpolation (computer graphics)Meshfree methodsMoving least squaresBoundary value problemDelaunay triangulationMathematical analysisStiffness matrixField (mathematics)Applied mathematicsFinite element methodSingular boundary methodGeometryClassical mechanicsBoundary element methodPure mathematics

Abstract

fetched live from OpenAlex

In Meshless natura1 neighbour Petrov-Galerkin method, The natural neighbour interpolation is used as trial function anda weak form over the local polygonal sub-domains constructed by Delaunay triangular is used to obtain the discretizedsystem of equilibrium equations, and it’s a new truly meshless method. This method simplified the formation of theequilibrium equations, facilitates the imposition of essential boundary conditions and the system stiffness matrix in thepresent method is banded and sparse. Efforts are made to study Meshless natural neighbour Pettrov-Galerkin Method,which is extended to solve the transient heat conduction. The numerical results show that the present method is quiteaccurate and stable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.396
Teacher spread0.371 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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